AIMC Topic: Humans

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Deep learning model to predict exercise stress test results: Optimizing the diagnostic test selection strategy and reduce wastage in suspected coronary artery disease patients.

Computer methods and programs in biomedicine
BACKGROUND: Cardiac exercise stress testing (EST) offers a non-invasive way in the management of patients with suspected coronary artery disease (CAD). However, up to 30% EST results are either inconclusive or non-diagnostic, which results in signifi...

Propensity-matched analysis of robotic versus sternotomy approaches for mitral valve replacement.

Journal of robotic surgery
To compare early and medium-term outcomes between robotic and sternotomy approaches for mitral valve replacement (MVR). Clinical data of 1393 cases who underwent MVR between January 2014 and January 2023 were collected and stratified into robotic MVR...

Home-based upper limb stroke rehabilitation mechatronics: challenges and opportunities.

Biomedical engineering online
Interest in home-based stroke rehabilitation mechatronics, which includes both robots and sensor mechanisms, has increased over the past 12 years. The COVID-19 pandemic has exacerbated the existing lack of access to rehabilitation for stroke survivor...

Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: This scoping review summarizes the applications of artificial intelligence (AI) and bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective was to explore supervised and unsupervised AI techniques and the...

Cross-Check QA: A Quality Assurance Workflow to Prevent Missed Diagnoses by Alerting Inadvertent Discordance Between the Radiologist and Artificial Intelligence in the Interpretation of High-Acuity CT Scans.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to implement and evaluate a quality assurance (QA) workflow that leverages natural language processing to rapidly resolve inadvertent discordance between radiologists and an artificial intelligence (AI) decision sup...

Multi-scale representation attention based deep multiple instance learning for gigapixel whole slide image analysis.

Medical image analysis
Recently, convolutional neural networks (CNNs) directly using whole slide images (WSIs) for tumor diagnosis and analysis have attracted considerable attention, because they only utilize the slide-level label for model training without any additional ...

Deep Learning-Based Fully Automated Segmentation of Regional Muscle Volume and Spatial Intermuscular Fat Using CT.

Academic radiology
RATIONALE AND OBJECTIVES: We aim to develop a CT-based deep learning (DL) system for fully automatic segmentation of regional muscle volume and measurement of the spatial intermuscular fat distribution of the gluteus maximus muscle.

The safe introduction of robotic surgery in a free-standing children's hospital.

Journal of robotic surgery
The aim of this study is to report the experience of implementing a pediatric robotic surgery program at a free-standing pediatric teaching hospital. A database was created to prospectively collect perioperative data for all robotic surgeries perform...

AI tools in Emergency Radiology reading room: a new era of Radiology.

Emergency radiology
Artificial intelligence tools in radiology practices have surged, with modules developed to target specific findings becoming increasingly prevalent and proving valuable in the daily emergency room radiology practice. The number of US Food and Drug A...